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Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review
PURPOSE: The purpose of this systematic review was to assess risk of bias in existing prognostic models of hospital-induced delirium for medical-surgical units. METHODS: APA PsycInfo, CINAHL, MEDLINE, and Web of Science Core Collection were searched on July 8, 2022, to identify original studies whic...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434879/ https://www.ncbi.nlm.nih.gov/pubmed/37590196 http://dx.doi.org/10.1371/journal.pone.0285527 |
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author | Snigurska, Urszula A. Liu, Yiyang Ser, Sarah E. Macieira, Tamara G. R. Ansell, Margaret Lindberg, David Prosperi, Mattia Bjarnadottir, Ragnhildur I. Lucero, Robert J. |
author_facet | Snigurska, Urszula A. Liu, Yiyang Ser, Sarah E. Macieira, Tamara G. R. Ansell, Margaret Lindberg, David Prosperi, Mattia Bjarnadottir, Ragnhildur I. Lucero, Robert J. |
author_sort | Snigurska, Urszula A. |
collection | PubMed |
description | PURPOSE: The purpose of this systematic review was to assess risk of bias in existing prognostic models of hospital-induced delirium for medical-surgical units. METHODS: APA PsycInfo, CINAHL, MEDLINE, and Web of Science Core Collection were searched on July 8, 2022, to identify original studies which developed and validated prognostic models of hospital-induced delirium for adult patients who were hospitalized in medical-surgical units. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was used for data extraction. The Prediction Model Risk of Bias Assessment Tool was used to assess risk of bias. Risk of bias was assessed across four domains: participants, predictors, outcome, and analysis. RESULTS: Thirteen studies were included in the qualitative synthesis, including ten model development and validation studies and three model validation only studies. The methods in all of the studies were rated to be at high overall risk of bias. The methods of statistical analysis were the greatest source of bias. External validity of models in the included studies was tested at low levels of transportability. CONCLUSIONS: Our findings highlight the ongoing scientific challenge of developing a valid prognostic model of hospital-induced delirium for medical-surgical units to tailor preventive interventions to patients who are at high risk of this iatrogenic condition. With limited knowledge about generalizable prognosis of hospital-induced delirium in medical-surgical units, existing prognostic models should be used with caution when creating clinical practice policies. Future research protocols must include robust study designs which take into account the perspectives of clinicians to identify and validate risk factors of hospital-induced delirium for accurate and generalizable prognosis in medical-surgical units. |
format | Online Article Text |
id | pubmed-10434879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-104348792023-08-18 Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review Snigurska, Urszula A. Liu, Yiyang Ser, Sarah E. Macieira, Tamara G. R. Ansell, Margaret Lindberg, David Prosperi, Mattia Bjarnadottir, Ragnhildur I. Lucero, Robert J. PLoS One Research Article PURPOSE: The purpose of this systematic review was to assess risk of bias in existing prognostic models of hospital-induced delirium for medical-surgical units. METHODS: APA PsycInfo, CINAHL, MEDLINE, and Web of Science Core Collection were searched on July 8, 2022, to identify original studies which developed and validated prognostic models of hospital-induced delirium for adult patients who were hospitalized in medical-surgical units. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was used for data extraction. The Prediction Model Risk of Bias Assessment Tool was used to assess risk of bias. Risk of bias was assessed across four domains: participants, predictors, outcome, and analysis. RESULTS: Thirteen studies were included in the qualitative synthesis, including ten model development and validation studies and three model validation only studies. The methods in all of the studies were rated to be at high overall risk of bias. The methods of statistical analysis were the greatest source of bias. External validity of models in the included studies was tested at low levels of transportability. CONCLUSIONS: Our findings highlight the ongoing scientific challenge of developing a valid prognostic model of hospital-induced delirium for medical-surgical units to tailor preventive interventions to patients who are at high risk of this iatrogenic condition. With limited knowledge about generalizable prognosis of hospital-induced delirium in medical-surgical units, existing prognostic models should be used with caution when creating clinical practice policies. Future research protocols must include robust study designs which take into account the perspectives of clinicians to identify and validate risk factors of hospital-induced delirium for accurate and generalizable prognosis in medical-surgical units. Public Library of Science 2023-08-17 /pmc/articles/PMC10434879/ /pubmed/37590196 http://dx.doi.org/10.1371/journal.pone.0285527 Text en © 2023 Snigurska et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Snigurska, Urszula A. Liu, Yiyang Ser, Sarah E. Macieira, Tamara G. R. Ansell, Margaret Lindberg, David Prosperi, Mattia Bjarnadottir, Ragnhildur I. Lucero, Robert J. Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review |
title | Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review |
title_full | Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review |
title_fullStr | Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review |
title_full_unstemmed | Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review |
title_short | Risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: A systematic review |
title_sort | risk of bias in prognostic models of hospital-induced delirium for medical-surgical units: a systematic review |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434879/ https://www.ncbi.nlm.nih.gov/pubmed/37590196 http://dx.doi.org/10.1371/journal.pone.0285527 |
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